@Benchmark
  int hashMultiset(int reps) {
    int sum = 0;
    for (int i = 0; i < reps; i++) {
      for (Object value : hashMultiset) {
        sum += value.hashCode();
      }
    }
    return sum;
  }

  @Benchmark
  int linkedHashMultiset(int reps) {
    int sum = 0;
    for (int i = 0; i < reps; i++) {
      for (Object value : linkedHashMultiset) {
        sum += value.hashCode();
      }
    }

        double sum = 0.0;
        for (double value : values) {
          sum += value;
        }
        return sum / values.length;
      }
    },
    KAHAN {
      @Override
      double mean(double[] values) {
        double sum = 0.0;
        double c = 0.0;
        for (double value : values) {
          double y = value - c;
          double t = sum + y;
          c = (t - sum) - y;

            {
               "datasource": {
                  "type": "prometheus",
                  "uid": "$datasource"
               },
               "expr": "sum (rate(istio_requests_total{reporter=~\"source|waypoint\",response_code!~\"5..\"}[$__rate_interval])) / sum (rate(istio_requests_total{reporter=~\"source|waypoint\"}[$__rate_interval]))"
            }
         ],
         "title": "Success Rate",
         "type": "stat"

    CacheStats sum = two.plus(one);
    assertEquals(124, sum.requestCount());
    assertEquals(64, sum.hitCount());
    assertThat(sum.hitRate()).isEqualTo(64.0 / 124);
    assertEquals(60, sum.missCount());
    assertThat(sum.missRate()).isEqualTo(60.0 / 124);
    assertEquals(56, sum.loadSuccessCount());
    assertEquals(52, sum.loadExceptionCount());
    assertThat(sum.loadExceptionRate()).isEqualTo(52.0 / 108);

        sum += array[index].hashCode();
      }
    }
    return sum;
  }

  @Benchmark
  int arrayFor(int reps) {
    int sum = 0;
    for (int i = 0; i < reps; i++) {
      for (Object value : array) {
        sum += value.hashCode();
      }
    }
    return sum;
  }

  @Benchmark
  int arrayListIndexed(int reps) {
    int sum = 0;
    for (int i = 0; i < reps; i++) {

    add(-1L);
  }

  /**
   * Returns the current sum. The returned value is NOT an atomic snapshot; invocation in
   * the absence of concurrent updates returns an accurate result, but concurrent updates that occur
   * while the sum is being calculated might not be incorporated.
   *
   * @return the sum
   */
  @Override
  public long sum() {
    long sum = base;
    Cell[] as = cells;
    if (as != null) {

      "version": "18eb4e529c60ec20ab243e2da3bcb52b2fd0d223",
      "sum": "eyuJ0jOXeA4MrobbNgU4/v5a7ASDHslHZ0eS6hDdWoI="
    },
    {
      "source": {
        "git": {
          "remote": "https://github.com/grafana/grafonnet.git",
          "subdir": "gen/grafonnet-v11.0.0"
        }
      },
      "version": "18eb4e529c60ec20ab243e2da3bcb52b2fd0d223",
      "sum": "6ycXhBvq/k7j01vaNiDSZcVsKikh01pfNH+2oauHgJg="
    },
    {

          "datasource": {
            "type": "prometheus",
            "uid": "${datasource}"
          },
          "editorMode": "code",
          "expr": "sum(irate(istio_requests_total{reporter=~\"$qrep\",destination_service=~\"$service\",response_code!~\"5.*\"}[5m])) / (sum(irate(istio_requests_total{reporter=~\"$qrep\",destination_service=~\"$service\"}[5m])) or on () vector(1))",
          "format": "time_series",
          "intervalFactor": 1,

        "name": "workload",
        "options": [],

		}
		var (
			hash = algorithm.New()
			msg  = make([]byte, 0, hash.Size()*hash.BlockSize())
			sum  = make([]byte, 0, hash.Size())
		)
		for i := 0; i < hash.Size()*hash.BlockSize(); i += hash.Size() {
			hash.Write(msg)
			sum = hash.Sum(sum[:0])
			msg = append(msg, sum...)
			hash.Reset()
		}
		if !bytes.Equal(sum, checksum) {